A different approach from typical persistent-memory MCPs. Instead of a local
SQLite + embeddings store, the memory lives as plain files in a .ai-memory/
directory you commit to your repo (facts.jsonl, decisions/\*.md, gotchas.md).
Git is the sync layer — what one Claude/Cursor/Cline learns about a repo, the
next session (or a teammate's agent) picks up automatically.
5 MCP tools: get_rep
Smart memory for AI agents. Solves the Karpathy problem: memories decay, topics are frequency-weighted, one-time questions don't become obsessions. 7 tools. Zero deps.
Local-first project memory for AI coding agents. Records failed attempts, fragile files, and decisions per repo, and warns the agent via hooks before it repeats a recorded mistake.
Provides persistent, local-first memory with knowledge graph and hybrid search for AI coding agents, reducing token usage by storing decisions, patterns, and codebase context.
Provides shared long-term memory and proactive suggestions across AI coding agents, enabling persistent user preferences and behavior rules that are remembered and applied across different tools. Includes memory capture, recall, extraction, and suggestion tools with a local-first and privacy-focused design.